Deepfakes are photos, videos or audio clips altered using
artificial intelligence to appear authentic, which experts have warned can
mislead or be completely false.
Facebook research scientists Tal Hassner and Xi Yin said
their team worked with Michigan State University to create software that
reverse engineers deepfake images to figure out how they were made and where
they originated.
"Our method will facilitate deepfake detection and
tracing in real-world settings, where the deepfake image itself is often the
only information detectors have to work with," the scientists said in a
blog post.
"This work will give researchers and practitioners
tools to better investigate incidents of coordinated disinformation using
deepfakes, as well as open up new directions for future research," they
added.
Facebook's new software runs deepfakes through a network to
search for imperfections left during the manufacturing process, which the
scientists say alter an image's digital "fingerprint."
"In digital photography, fingerprints are used to
identify the digital camera used to produce an image," the scientists
said.
"Similar to device fingerprints, image fingerprints are
unique patterns left on images... that can equally be used to identify the
generative model that the image came from."
"Our research pushes the boundaries of understanding in
deepfake detection," they said.
Microsoft late last year unveiled software that can help
spot deepfake photos or videos, adding to an arsenal of programs designed to
fight the hard-to-detect images ahead of the US presidential election.
The company's Video Authenticator software analyzes an image
or each frame of a video, looking for evidence of manipulation that could be
invisible to the naked eye.